data governance

  • The Hidden Costs of Data Contracts

    The Hidden Costs of Data Contracts

    Daniel Linstedt

    Data contracts are often presented as a new approach to managing data exchange, but they largely rename established enterprise functions related to data capture, transformation, and delivery. This article clarifies the distinct responsibilities and control boundaries within these components, highlighting the risks of conflating labeling with architecture. Understanding this history reveals persistent governance challenges and…

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  • Analytics Modernization and the Hidden Cost of Trust Erosion

    Analytics Modernization and the Hidden Cost of Trust Erosion

    Daniel Linstedt

    Analytics modernization often equates speed and adoption with success, but this can conceal growing gaps in accountability and decision defensibility. Decentralized analytics practices fragment meaning and proof obligations, eroding trust silently over time. Deferred governance decisions compound latent costs that surface only at scale or audit. Leadership accountability defaults upward when controls are insufficient, making…

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  • Why AI Does Not Eliminate the Need for Data Modeling

    Why AI Does Not Eliminate the Need for Data Modeling

    Daniel Linstedt

    AI initiatives often fail to scale safely without disciplined information management that preserves meaning, lineage, and accountability. This failure is systemic, reflecting deferred decisions and fragmented authority rather than AI technology limitations. Data Vault should be understood as a system of information management that stabilizes semantic consistency across organizational change. Skepticism about data modeling arises…

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  • Modernization That Appears Successful Until Scrutiny

    Modernization That Appears Successful Until Scrutiny

    Daniel Linstedt

    Modernization efforts often appear successful based on delivery metrics but conceal growing liabilities due to lack of auditable evidence and clear accountability. Scaling and AI amplify these risks by increasing the impact of semantic drift and data integrity issues. Defensibility under audit requires explicit proof obligations and ownership, which are frequently deferred, creating governance gaps.…

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  • Poison Data and Espionage, AI, ML, Deep Learning

    Poison Data and Espionage, AI, ML, Deep Learning

    Daniel Linstedt

    In Episode 2 of Unlocking the Data Vault, I mentioned the term: Poison Data.   I must admit, it’s a cool term, and I also admit the term is not mine.  It stems from espionage in an attempt to poison data that feeds AI / ML and deep learning algorithms.  It distorts documents, imagery, video, and

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  • Episode 2: Defining and Solving Business Risks

    Episode 2: Defining and Solving Business Risks

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    Cindi Meyersohn

    Join Us for Unlocking the Vault with Dan Linstedt Audit compliance, global security, distributed privacy policy, and insuring raw data is available for data scientists are just a few of the business risks we face…but are all tackled with the DV2.0 methodology. In this episode, Dan outlines some of the most vexing problems encountered by business

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